How analysis empowered by data is driving Covid predictions in India and worldwide

Dr Kanav Kahol, 

The world failed to prevent the Novel Coronavirus from spreading initially, which turned into a fatal pandemic. Henceforth, quick strategies became crucial to getting rid of the virus along with its consequences. The healthcare industry worldwide took a step towards big data and predictive analytics tools to comprehend the characteristics of the disease, risk factors, and diagnostics.

This advanced technology, along with Artificial Intelligence and Machine Learning, could help us predict propensities of the clinical pathways, facilitate the treatment, and defy the infection. As a result, medical teams are able to manage and assign medical resources adequately.

How Data Analytics Paved the Way for the Healthcare Industry to Mitigate COVID-19?

With increased data sharing and access, the COVID-19 outbreak has prompted researchers to integrate and improve data analytics tools in order to alleviate its impacts. These near-real-time tools can invariably cull data from sources that are helping scientists, epidemiologists, healthcare professionals, and policymakers globally.

Most importantly, predictive analytics has facilitated medical organizations to prioritize care management outreach to people at a higher risk of infection. Hence, demand for analytics rose. Our data scientists are continuously striving to refine the analytical models to enhance predictive analytics accuracy eventually.

Let’s check out in-detail how data-driven strategies enable people throughout the globe to fight off the pandemic.

Evaluating Future Demands

The anticipation of future demands is one of the most critical benefits of leveraging data analytics. The provided outcome can help initiate preventive measures for hospitals. It involves ICU beds, ventilators, and PPE kits. Governments across various countries are also using big data-powered solutions to balance the production and distribution of N95 masks and other medical equipment.

Gender, age, geographical location are some of the variables considered using Data Visualization and Python systems. The analytics models design most probable, best case, and worst-case scenarios as per the changing data and real-time events. Clinical trial operations are the highest advantage during this drastic time with data’s ability to connect us more promptly with patients.

For instance, healthcare sectors can create a plan to organize more beds or other medical resources if there is a surge hospital in COVID-19 cases.

Self-assessment Devices

With the development of self-assessment devices, users can check their symptoms and seek instant medical care if needed. The insightful data accumulated from GPS analyses of population movement also eventually help track whether the population is following set precautions or not.

Additionally, researchers could capably predict that other than cough and fever, loss of smell and taste are also vital symptoms of the contagious disease. They got insight from data entered by millions of people on their mobiles, reporting their symptoms on a specific day.

Faster Drug Discovery

Drug development is undoubtedly and most often is a process that takes decades to launch into the market successfully. Besides, there are higher chances of failure that even incurs enormous costs. However, researchers found potential treatments for COVID-19 leveraging ML and AI devices early in the pandemic. Algorithms computationally produce, screen, and optimize a number of therapeutic antibodies.

Today, our various drug discovery organizations are utilizing these technologies to predict which new drug-like molecules and existing drugs could treat the infection. Hence, you can significantly expedite the drug development process and invent cheaper antivirals using AI and deep learning technology.

Preventing Virus Transmission

Scientific and medical teams working on diagnostic systems can have improved diagnosis of the infection through the Linearfold algorithm. It’s a quicker and time-saving model than conventional RNA folding algorithms to forecast a virus’s secondary RNA structural changes between homologous COVID-19 RNA sequences. Hence, scientists get more insight into the development of viruses across different species. Ultimately, this procedure can save lives through faster and before-time identification of effective treatments.

In fact, Bluedot was one of the first organizations that forecasted the outbreak before the WHO in December using Big Data, Natural Language Processing, and Machine Learning.

Bottom Line…

We know even after extensive data and predictive algorithms, the virus has still not worn out completely. Yet, we have hope. The insight acquired on COVID-19 patient surges and disease patterns can be the torchbearers of eradicating the virus.

Analytics is still a good bet; when situations get intricate. The advanced approach opened a plethora of opportunities to make data impactful for both healthcare professionals and society.

(The author is a renowned healthcare innovator who is a former PhD scientist and professor from Arizona State University and Mayo Clinic USA. He started Divoc Health in partnership with Christopher Egerton Warburton (Edge) form Lions Global Head Partners UK. Views expressed are personal and do not reflect the official position or policy of the Financial Express Online.)